Optimizing sample preparation for anatomical determination in the ...

Optimizing sample preparation for anatomical determination in the hippocampus of rodent brain by ToF-SIMS analysis Tina B. Angerer, Amir Saeid Mohammadi, and John S. Fletcher Citation: Biointerphases 11, 02A319 (2016); doi: 10.1116/1.4941064 View online: http://dx.doi.org/10.1116/1.4941064 View Table of Contents: http://scitation.aip.org/content/avs/journal/bip/11/2?ver=pdfcov Published by the AVS: Science & Technology of Materials, Interfaces, and Processing Articles you may be interested in Improved mass resolution and mass accuracy in TOF-SIMS spectra and images using argon gas cluster ion beams Biointerphases 11, 02A321 (2016); 10.1116/1.4941447 Imaging of amyloid-β in Alzheimer's disease transgenic mouse brains with ToF-SIMS using immunoliposomes Biointerphases 11, 02A312 (2016); 10.1116/1.4940215 Lipid analysis of eight human breast cancer cell lines with ToF-SIMS Biointerphases 11, 02A303 (2016); 10.1116/1.4929633 3D chemical characterization of frozen hydrated hydrogels using ToF-SIMS with argon cluster sputter depth profiling Biointerphases 11, 02A301 (2016); 10.1116/1.4928209 Assessment of different sample preparation routes for mass spectrometric monitoring and imaging of lipids in bone cells via ToF-SIMS Biointerphases 10, 019016 (2015); 10.1116/1.4915263

Optimizing sample preparation for anatomical determination in the hippocampus of rodent brain by ToF-SIMS analysis Tina B. Angerer Department of Chemistry and Molecular Biology, University of Gothenburg, SE-412 96 Gothenburg, Sweden

Amir Saeid Mohammadi Department of Chemistry and Chemical Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden

John S. Fletchera) Department of Chemistry and Molecular Biology, University of Gothenburg, SE-412 96 Gothenburg, Sweden

(Received 15 November 2015; accepted 20 January 2016; published 8 February 2016) Lipidomics has been an expanding field since researchers began to recognize the signaling functions of lipids and their involvement in disease. Time-of-flight secondary ion mass spectrometry is a valuable tool for studying the distribution of a wide range of lipids in multiple brain regions, but in order to make valuable scientific contributions, one has to be aware of the influence that sample treatment can have on the results. In this article, the authors discuss different sample treatment protocols for rodent brain sections focusing on signal from the hippocampus and surrounding areas. The authors compare frozen hydrated analysis to freeze drying, which is the standard in most research facilities, and reactive vapor exposure (trifluoroacetic acid and NH3). The results show that in order to preserve brain chemistry close to a native state, frozen hydrated analysis is the most suitable, but execution can be difficult. Freeze drying is prone to produce artifacts as cholesterol migrates to surface, masking other signals. This effect can be partially reversed by exposing freeze dried sections to reactive vapor. When analyzing brain sections in negative ion mode, exposing those sections to NH3 vapor can re-establish the diversity in lipid signal found in frozen hydrated analyzed sections. This is accomplished by removing cholesterol and uncovering sulfatide signals, C 2016 American Vacuum Society. allowing more anatomical regions to be visualized. V [http://dx.doi.org/10.1116/1.4941064] I. INTRODUCTION Time-of-flight secondary ion mass spectrometry (ToFSIMS) imaging was introduced in the middle of the 20th century,1 but is in constant development with technological progress being made every year, improving resolution and sensitivity to higher mass secondary ions. Enhancing the breadth of information accessible with biological sample analysis is a major driving force for these developments. For many years, SIMS only worked well for inorganic or atomic species and small molecules but due to the implementation of cluster (Au3, Bi3),2,3 polyatomic (SF5, C60),4–6 and most recently, giant gas clusters as primary ion beams,7 it is now possible to collect signals from intact biological molecules and display their distribution at subcellular resolution.8–10 Gas cluster ion beams (GCIBs) have been shown to provide a means of more gently removing material from the sample surface resulting in less fragmentation. This reduces the ion beam induced chemical damage in the sample compared to smaller primary ions.11,12 Higher energy clusters, such as the 40 keV beam used for this study, have recently been shown to produce a significant enhancement of lipid signal during tissue analysis compared to the previous state of the art C60 beams.8 ToF-SIMS uses a beam of primary ions to scan over a surface, sputtering secondary ions from the sample to reveal its a)

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chemical properties. This generates a chemical map of the sample, displaying the location and intensity of the analyzed molecules. However, the surface sensitivity of this technique and the requirements for high vacuum analysis conditions present challenges for ensuring that the resulting chemical distributions represent the native biology of the sample. Lipids fulfil a variety of functions in the brain (and elsewhere in the body) of which an overview can be found in a review published in Nature Reviews Neuroscience.13 Changes in lipid content in the brain have been linked to a range of neurodegenerative diseases, so methods for accurately detecting these changes with high specificity and spatial resolution are vital. When studying the distribution of lipids in the brain, ToF-SIMS has the unique capability to image, identify, and provide relative quantification of a great number of them simultaneously without the need for labels or special sample preparation (for example, applying a matrix for matrix assisted laser desorption ionization analysis, MALDI) and has been used to good effect in numerous studies of cell and tissue samples.14–16 However, it has been recognized that ToF-SIMS studies in certain brain regions produce results contradictory to other techniques often where cholesterol signals are very high.17,18 In this study, we show that sample treatment can have severe effects on the relative intensities of different groups of lipids. Being aware of those effects is crucial when planning and conducting a ToF-SIMS experiment and interpreting the results in terms of biological

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02A319-2 Angerer, Mohammadi, and Fletcher: Optimizing sample preparation for anatomical determination

significance. We investigate signal changes, mainly in negative ion mode, due to a variety of sample treatments with a focus on ammonia (NH3) vapor exposure. Recently, we reported on spectral changes in brain sections exposed to trifluoroacetic acid (TFA) vapor with a focus on signal improvement of protonated secondary ion species in positive ion mode.9 TFA is a common component in MALDI matrices which has also been used in desorption electrospray ionization experiments.19 While acidic TFA vapor acts as a proton donor, increasing protonated [MþH]þ species in positive ion mode, basic ammonia vapor should act as a proton acceptor, therefore should increase deprotonated [MH] species in the ToF-SIMS spectra. Ammonia vapor has been previously used by Vaidyanathan and coworkers to successfully increase the intensity of deprotonated secondary ion species from small plant metabolite cocktail drops.20 In MALDI experiments, ammonia salts have shown to provide the samples with negative charges.21 Now we aim to investigate if intact lipid signals generated from brain sections with ToF-SIMS can be increased as well. We analyzed the hippocampal formation and surrounding areas in consecutive rodent brain sections to assess the ability of ToF-SIMS to identify and distinguish different anatomical features based on characteristic lipid profiles. The tissue sections underwent different forms of sample treatment: cryosectioning and analyzing the section frozen hydrated (FH) without drying them or exposing them to ambient air at any time during the experiment; cryosectioning, then freeze drying (FD); after freeze drying, exposing the section to ammonia vapor for 15, 30, or 60 min (15, 30, 60_NH3) inside a desiccator; or, after freeze drying, exposing the section to TFA vapor for 30 min (TFA) inside a desiccator. Since this study focuses on the effect of ammonia treatment versus the standard freeze drying, those measurements have been performed three times on two different days but still on the same brain. Each treatment had different, but reproducible, effects on the studied brain areas. A. Brain regions, cell types, and significance 1. Hippocampal formation

Scientists have been curious about the hippocampal formation for decades, because of its intricate anatomy and the fact that it is a highly preserved brain region throughout the animal kingdom, in structure as well as function. In many vertebrates, new neurons are produced in this brain region throughout adulthood.22–24 A great variety of neuronal cell types are found within the hippocampal formation, building up its structures, like granule cells in the granular layer and pyramidal cells in the pyramidal layer, all of which play important roles in a number of diseases (for example, Alzheimer’s disease).25 Neurogenesis was thought to happen only in the developing brain, but already in the 1960s, studies in rats showed, that new neurons are formed within the granular layer of the dentate gyrus, a part of the hippocampal formation.26 Since then it has been discovered that the dentate gyros is potentially involved in associative memory Biointerphases, Vol. 11, No. 2, June 2016

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formation and enhancing neurogenesis is possible by performing specific learning tasks.27 The pyramidal cell layer is of interest since it is divided in different sections, possibly fulfilling different functions which are currently under investigation.28 For interest, a complete list of all currently known types of neurons in the hippocampal formation can be found in the supplementary material.29 2. Thalamus (lateral geniculate nucleus)

The thalamus is a centrally located brain structure containing a number of nuclei, separated by thin layers of myelin.30 The major role of the thalamus is to gate and modulate the information flow to the cortex via inhibitory neurons (GABAergic cells). For example, before visual information from the retina reaches the visual cortex, it is relayed through one of its nuclei, the lateral geniculate nucleus of the thalamus.31 3. Midbrain

The midbrain represents the largest assembly of dopamine containing neurons.32 Midbrain dopaminergic (mDA) neurons are controlling key functions of the brain, such as voluntary movement. Their involvement in Parkinson’s disease and other mental disorders make mDA neurons an interesting target for clinical studies.33 The capability of imaging ToF-SIMS to study the distribution and changes of a great variety of lipids in all those regions at the same time makes it a valuable tool to expand our knowledge on lipid changes in different cell types and their involvement in brain function and disease. In this study, we assess the role of different sample preparation approaches to distinguish the chemical differences between these important brain areas. II. EXPERIMENTAL SETUP AND METHODOLOGY A. Tissue preparation

To ensure the least possible amount of natural variation for the detected chemical signals, all analyzed tissues are consecutive sections stemming from the same brain. Young male Zucker Fa/ (lean) rat brain was dissected and frozen in liquid nitrogen, then stored at 80 C until sectioning. Sagittal rat brain tissue slices with 6 lm thickness were cut at 20 C using a cryomicrotome (Leica CM1520) filled with dry argon gas. Sections were thaw-mounted on indiumtin-oxide (ITO) coated glass slides. For freeze-dried brain analysis, samples underwent a crude freeze drying process. After sectioning at 20 C, they were placed on a precooled steel plate and gradually brought to the room temperature in a vacuum desiccator. For simplicity, those sections will be referred to as freeze dried throughout the manuscript. The frozen hydrated tissue sections were analyzed immediately after the sectioning. Sample transportation and insertion into the SIMS instrument was carried out under argon gas. This is possible due to an argon gas filled glovebox mounted on top of the sample insertion port, for this purpose. During


frozen hydrated analysis, the analysis stage of the SIMS instrument was kept at a steady temperature below 100 K. B. SEM imaging

Scanning electron microscopy (SEM) was performed using a Zeiss ULTRA 55 FEG scanning electron microscope (Zeiss, Jena, Germany). The images were obtained using a 1 keV beam to minimize charging of the tissue sample. C. NH3/TFA treatment

TFA treatment has been performed as described previously.9 Briefly, freeze dried brain tissue sections were exposed to TFA vapor prior to SIMS analysis. Similarly, target tissue sections were exposed to NH3 generated from 25% ammonia solution (MERCK, 105428 Ammonia solution 25%). A glass petri dish containing 300 ll of solution was placed at 1 cm distance from the sample in a sealed desiccator (diameter 250 mm). Exposure durations for NH3 were 15, 30, or 60 min and for TFA 30 min. Data for 15 min exposure produced results very similar to 30 min. These data (15 min exposure) are included in principal components analysis (PCA) models but for simplicity and clarity not included in other figures. D. ToF-SIMS imaging

ToF-SIMS analyses were performed using a J105 instrument (Ionoptika, Ltd., UK). The J105 has been described in detail elsewhere.34,35 Briefly, the instrument uses a quasicontinuous primary ion beam to produce a stream of secondary ions that are sampled by a linear buncher prior to ToF measurement. In this study, a 40 keV GCIB was used to bombard the sample with clusters of Corgon 8 (8% CO2 in Ar) gas (AGA, Sweden). Nominal cluster size was 4000; for

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simplicity, this will be written as Ar4000 throughout the remainder of the manuscript although the gas used to produce the beam contained 8% CO2 in all measurements. Spectra were recorded over a mass range of 80–2500 Da. Large area images were generated by producing a series of individual image “tiles” that were stitched together automatically by the acquisition software. Each tile comprised 32 32 pixels. In total, images were generated with 160 160 pixels covering an area of 4 4 mm2 with a primary ion dose density of 1 1012 ions/cm2 in negative and positive ion mode. The beam diameter was much smaller pixel size; therefore, the lateral resolution in the images is pixel limited. The beam was dithered over each pixel to ensure an even primary ion dose density. E. Data treatment 1. Images

Multivariate analysis (PCA) on ToF-SIMS images was performed in MATLAB (The MathWorks, Inc.) in two steps. In the first step, PCA was performed on the whole image. To avoid contribution of inorganic species from the ITO-coated glass substrate in images where the tissue did not cover the analyzed area completely, background subtraction based on the first principal component was performed, eliminating all substrate containing pixels. Prior to the second step, the spectra contained in the remaining image pixels were treated as such. For PCA the mass range 200–2000 Da. was selected and the time resolution down sampled to 10 ns to reduce computer memory requirements. The square root of the mass spectrometry signal intensity was used to reduce the dynamic range of the data set. PCA was then applied again to this reduced dataset. Output images are displayed in a red–green color scheme (Fig. 1). The red areas are represented by negative loadings (later referred to

FIG. 1. Results for imaging PCA performed on a frozen hydrated brain section, analyzed by ToF-SIMS at a stable temperature of 100 K in negative ion mode. Shown are principal components (a) 1, (b) 4, (c) 5, (e) 6, (f) 8, and (g) 10 as these display greatest chemical variety in and around the hippocampal formation. Positive scoring pixels in each PC are displayed in green, negative pixels in red. Pixels with little or no variation in this PC are black. (d) An image retrieved from the Allen Developing Mouse Brain Atlas, with manually added labels, that displays structures and assignments according to histology of the different brain regions that can be found in the PCA images. (h) Red/green/blue overlay ToF-SIMS image showing chemical variety in different brain regions; the peaks used to generate this image are m/z 766.53 PE(38:4) [MH], m/z 885.54 PI(38:4) [MH] and m/z 906.63 Ch24:0 sulfatide [MH]. The white scale bar represents 1 mm. Biointerphases, Vol. 11, No. 2, June 2016


as PC), and the green areas by positive loadings (PCþ) with intense red/green showing a high scoring region/great variance for this principal component while darker tones and black signify low or no variance in this region. For the loadings spectra, the same color scheme was adapted. 2. Spectra

Multivariate analysis (PCA) on ToF-SIMS spectra was performed using SIMCA (Umetrix, Sweden). Spectra originating from these different brain regions—fiber tracts, granular and pyramidal layer, isocortex (visual area), midbrain, molecular layer, stratum radium and thalamus, or more specifically the lateral geniculate dorsal nucleus of the thalamus—were extracted from ToF-SIMS images (the underlined letters are used to refer to those areas in supplementary Fig. 1 (Ref. 29) and all PCA models and tables). To reduce data size and the possible influence of artifacts (e.g., slight calibration differences), spectra were down binned to 0.1 Da and reduced to m/z 100–2100. Also, all spectra were normalized to their total intensity to compensate for slight variations in the area of selected anatomical regions in different slices of brain tissue. Overlaid absolute and normalized spectra from different regions of the tissue analyzed either FH or freeze dried (FD) are displayed in supplementary Fig. 1 (Ref. 29), with variations in relative peak intensities clearly visible. The two examples show three freeze dried spectra from thalamus (Tha) and stratum radium (Rad) displaying only little variation after data treatment, while differences to the frozen hydrated spectra remain largely unchanged. These binned and normalized spectra were imported into SIMCA where PCA-X was performed on the whole, as well as subdatasets. Since we were interested in interpreting the PCA loadings to identify chemical changes (the presence of different chemicals as well as the intensity), “centric scaling”, which in essence only mean centers the data, was chosen. Other scaling methods (univariate, Pareto) were tested and showed similar but less clear separation patterns. We believe the requirement for additional scaling was removed due to the reduced overall dynamic range in the data as the very low mass peaks were not present (Naþ, Kþ, POx, etc.,) while the GCIB provided increased signal at higher mass (intact lipids). Raw spectra are shown in supplementary Fig. 1 (Ref. 29). SIMCA is model generation software where the cumulative (cum) values RX2 and Q2 are used to describe the quality of the generated PCA models. R2 (X with PCA) is the percentage of variation of the training set, explained by the model. A large R2 (close to 1) is a necessary condition for a good model. Q2 is the percentage of variation of the training set predicted by the model according to cross validation. Q2 indicates how well the model predicts new data. Poisson scaling is commonly applied to ToF-SIMS data prior to PCA; however, the J105 uses an analog to digital counting system not a single ion counting time to digital converter system that other ToF-SIMS instruments normally Biointerphases, Vol. 11, No. 2, June 2016

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use, so Poisson scaling may not be correct and could introduce artifacts in the data.36,37 III. RESULTS AND DISCUSSION A. Multivariate analysis of image data to find distinguishable brain regions

Imaging PCA was used as a first step to distinguish different regions in the brain due to their unique chemical signatures. Figure 1 shows principal components (PC) 1, 4, 5, 6, 8, and 10 of imaging PCA on the frozen hydrated data set, acquired in negative ion mode. The corresponding loadings can be found in supplementary Fig. 2 (Ref. 29). The peaks responsible for the separation are labeled and discussed in the 3rd paragraph of Sec. III B since the same peaks caused the separation in the spectral PCA. These principal components highlight areas which have been assigned as fiber tracts (PC1), granular and pyramidal layer (PC5þ), isocortex (PC1þ/PC8), midbrain (PC1/PC10), molecular layer (PC4þ/PC10), stratum radium (PC4/PC10þ), and thalamus (PC4/PC6). The anatomical assignments were made by comparison with the Allen Developing Mouse Brain Atlas, dataset P56, sagittal [Fig. 1(d)]. In order to ensure that those areas contain different chemistry and were not separated due to artifacts, PCA results were compared with the original SIMS data using peaks identified by PCA [Fig. 1(h)]. In positive ion mode imaging, PCA was able to distinguish similar features but displayed less chemical diversity. The granule/pyramidal cells are mainly distinguished due to their lower signal in positive ion mode, and the fiber tracts are dominated by the cholesterol signal in the freeze dried data set. The results from imaging PCA on the freeze dried data set are displayed in supplementary Fig. 3 (Ref. 29). This data suggest that sodiated phosphocholine (PC) lipid species {m/z 765.5 [PC(32:0) þ Na]þ, m/z 782.5 [PC(34:1) þ Na]þ and m/z 810.6 [PC(36:1) þ Na]þ} are mainly found in the isocortex while potassiated species {m/z 713.4 [PC(32:0-TMA) þ K]þ, m/z 739.5 [PC(34:1TMA) þ K]þ and m/z 798.5 [PC(34:1) þ K]þ, where TMA is the trimethylamine, N(CH3)3, moiety} can be found in the hippocampal formation. B. Multivariate analysis of spectra comparing brain regions and sample treatment

Spectra were extracted from different regions with the greatest possible accuracy, and the exact origin on the brain section for each spectrum was documented. An overlay of normalized spectra from all brain regions comparing frozen hydrated, freeze dried, and ammonia treatment can be found in the supplementary Fig. 4 (Ref. 29) displaying overall spectral changes. All collected spectra represent a large dataset which is difficult to analyze manually; therefore, PCA was performed to elucidate trends in chemical changes. PCA on the whole dataset (all brain regions and treatments) shows a general trend to group together and partially separate spectra from different brain regions along the first principal component (PC1) axis, which represents the greatest variation in the


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FIG. 2. Results for PCA-X data analysis generated from spectra of all brain areas and sample treatments. PC1 vs PC2, (a) color coded according to different brain regions (specified earlier), (b) color coded according to different sample treatments (15, 30, and 60 min of ammonia exposure, FD: freeze dried, FH: frozen hydrated, TF: TFA exposure). PC1 vs PC5, (c) color coded according to different brain regions, (d) color coded according to different sample treatments. This model consists of 14 principal components in total accounting for 99.5% of the variation in the dataset and a high value for predictability [R2X(cum) 0.995, Q2(cum) 0.997].

data set accounting for 70% of variation in the model (PC1 R2X 0.699, Q2 0.645). However, there are a few exceptions, e.g., “15 Mol,” but this is most likely due to this region being cut off in the image, and therefore, the spectra could not be taken from exactly the same region in all images. Data from the TFA exposed sample show the biggest variation compared to the rest of the data. A discussion on changes due to TFA treatment will follow in Sec. F. The second principal component (PC2), which represents the second largest variation in the data [PC2 R2X(cum) 0.823, Q2 0.749], shows a trend to group the spectra together according to sample treatment (Fig. 2). Since the chemical similarities for each brain region outweighs the differences caused by the sample treatment, we can conclude that in general with ToF-SIMS, it is possible to distinguish anatomically different regions in rodent brain based on the chemical variance accessible by SIMS. This may be different for different sample types with different chemistries. A scores plot for PC1 versus PC5 displays a grouping of the spectra solely based on brain regions without a recognizable pattern according to sample treatment. The results of the imaging and spectral PCA show that midbrain, thalamus, fiber tracts, and granular/pyramidal layer Biointerphases, Vol. 11, No. 2, June 2016

can be distinguished according to their chemical differences detectable by ToF-SIMS. In image PCA isocortex, molecular layer and stratum radium can be separated from the other brain regions and appear to be different. When spectral PCA was performed on the whole dataset, they seem to be chemically too similar to be separated from each other. For certain subsets of the data, this is different and discussed below. Data from similar brain regions, which have undergone the same sample treatment, tend to score together (or in close proximity for similar sample treatments, ammonia 15, 30, and 60 min) in the model, although the analysis was conducted on different days. This indicates a good reproducibility. Interestingly, this model suggests that TFA treatment and FD produce spectra more similar to FH than ammonia treatment (15, 30, and 60 min). The loadings for PC1, 2, and 5 (Fig. 3) provide the information on which signals these separations are based on. PC1 mainly separates sulfatide (Sulf.) containing areas (regions: Fib, Mid, Tha; peaks: m/z 888.6 C24:1 Sulf. [MH], m/z 906.6 Ch24:0 Sulf. [MH], where h indicates the presence of a hydroxylated fatty acid chain) from areas high in phosphoinositol (PI) lipid, sphingomyelin (SM) lipid, and saturated fatty acid (FA)


FIG. 3. Loadings for (a) PC1, (b) PC2, and (c) PC5 explaining the results for PCA-X data analysis generated from spectra of all brain areas and sample treatments in negative ion mode. The most significant signals for the separation are labeled.

signals {regions: Iso, Rad, Mol; peaks: m/z 225.2 FA(16:0), m/z 283.3 FA(18:0), m/z 715.6 SM(35:1), m/z 885.6 PI(38:4) [MH]}. Separation according to PC2 is also based on sulfatides (ammonia treatment peaks: m/z 806.6 C18:0 Sulf. [MH], m/z 888.6 C24:1 Sulf. [MH]) versus other lipid species like phosphoserine (PS) and phosphatidic acid (PA) (FH and TFA treatment peaks: m/z 747.5 PA(40:6) [MH], m/z 834.5 PS(40:6) [MH], m/z 885.5 PI(38:4) [MH]). In PC5, among other signals, cholesterol (m/z 385.4) plays a significant role for the separation. PCA on subdatasets shows largely the same trends as PCA on whole dataset (PCA on ammonia data supplementary Fig. 5). The PCA model on ammonia data is able to Biointerphases, Vol. 11, No. 2, June 2016

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distinguish between isocortex and molecular layer by the fifth PC. Those areas could not be distinguished in the model for the complete data. PCA on the freeze dried dataset cannot separate them until the seventh PC. When comparing red, green, blue overlay (Fig. 4) and single ion images (supplementary Fig. 6) for frozen hydrated, freeze dried, and ammonia treated brain slices, one can see that although the displayed signals {m/z 885.5 PI(38:4) [MH], (gangliosides) m/z 1544.9 GM1(36:1) [MH], m/z 1572.9 GM1(38:1) [MH]} show the same distribution in all three images, differences in chemical signals between those areas (isocortex and molecular layer) are more pronounced for frozen hydrated and ammonia treatment, when compared to freeze dried analysis (Fig. 4). This could explain why imaging PCA on frozen hydrated brain and spectra PCA for only ammonia treatment can distinguish between isocortex and molecular layer but PCA on the whole dataset and on the freeze dried dataset struggles to do so. PCA and spectral comparisons were also performed for positive ion mode spectra, but on a smaller dataset, comparing isocortex, stratum radium and fiber tracts. The spectra and results for the PCA analysis are displayed in supplementary Fig. 7. The PCA model is heavily influenced by the high cholesterol signal in the fiber tracts of the freeze dried spectra. PC1 mainly distinguishes between no/little cholesterol and high cholesterol and accounts for almost 90% of variance in the data. In the fiber tracts spectra of the ammonia treated brain sections, cholesterol signal is reduced but still present, unlike after TFA treatment, where it vanishes completely.9 We have previously presented a hypothesis that crystals often observed on the surface of the white matter regions of rodent brain are from cholesterol migration and accumulation. SEM images of ammonia treated brain sections show that these cholesterol crystals are still present but appear to be slightly reduced compared to freeze dried brain sections (supplementary Fig. 8). PC2 shows that in the frozen hydrated and ammonia treated brain sections, ceramide signals (galactoceramide, GalCer) are increased {m/z 264.3 ceramide fragment, m/z 826.6 [GalCer(42:1) þ H]þ, m/z 850.7 [GalCer(42:1) þ Na]þ, m/z 866.6 [GalCer(42:1) þ K]þ}. Stratum radium and isocortex produce similar signals for all sample treatments. In summary, it is evident that ammonia treatment does not have a detrimental effect on ToF-SIMS analysis in positive ion mode apart from the partial cholesterol removal. The PCA model indicates that (probably due to this removal) ammonia exposure results in the generation of spectra more similar to that from frozen hydrated analysis. C. Changes in lipid ratios due to sample treatment in all brain regions

The loadings for the PCA models indicate the general contribution and changes of different signals in the studied brain regions due to sample treatment but identifying the specific information for individual treatments/areas is challenging. In order to gain a better understanding of the changing mechanisms of different sample treatments, we calculated the ratios


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FIG. 4. ToF-SIMS images comparing (a) frozen hydrated (FH), (b) freeze dried (FD), and (c) ammonia treatment (NH3) with focus on the brain areas isocortex and molecular layer. The peaks used to generate this red green blue overlay image are m/z 885.5 PI(38:4) [MH], m/z 1544.9 GM1 (36:1) [MH], and m/ z 1572.9 GM1 (38:1) [MH]. The white scale bar represents 1 mm. All data were acquired using 40 keV Ar4000þ, ion dose: 1 1012 ions/cm2, negative ion mode.

of peak change for each peak and brain area separately where each spectra was divided by an average spectrum from the freeze dried data set from the same area {e.g., for the 60 min NH3 exposure data from the midbrain: Ratio ¼ (60_i_Mid)/ [(FD_i_Mid þ FD_ii_Mid þ FD_iii_Mid)/3]}. We chose to compare with the freeze dried sample treatment, since it is the most commonly used. For the calculations, the normalized spectra were used. A peak window of 0.3 Da was chosen. In most cases, this peak window contains one detected species. Only for cholesterol at m/z 385.4, we detected a peak in the TFA treated sections of a similar mass but showing an even distribution over the whole area [supplementary Fig. 9(d)]. We are confident that this peak is not cholesterol, because in the positive ion mode, we detect no cholesterol signals at all in TFA treated brain slices. The ratios were calculated over the whole spectrum (m/z 100–2100), but for clarity, 93 peaks that were either the most intense peaks or showed the greatest variation between regions and sample preparation were selected to display the trends for signal changes (Fig. 5). The table in Fig. 5 is simplified, instead of displaying exact ratios different colors for up or down-regulated signals are used and certain lipid species are grouped together, sorted from low to high mass. For a detailed list of peaks, replica of the 60 min ammonia treatment and numerical values for each ratio, see supplementary Table 1. Figure 5 illustrates in a comprehensive manner what was indicated by the PCA loadings in Fig. 3. Peaks that are decreased compared to the freeze dried data set are displayed in shades of red; peaks that are enhanced are highlighted in shades of green and blue. Peaks that show no significant changes (because the peak intensities are similar to the freeze dried data set, or this peak does not show up in the freeze dried and the comparing data set) are white. Gray indicates missing data (60_iii_NH3 Iso). Overall, the molecular layer and isocortex show the least changes for any sample treatment. Fiber tracts and midbrain change the most. A detailed discussion for all observed changes follows in Secs. D–F. D. Changes due to ammonia treatment

The first striking feature is the increase in signal for almost all the sulfatide species detected. This is most Biointerphases, Vol. 11, No. 2, June 2016

pronounced for the 60 min ammonia treatment in the granular layer, stratum radium, and midbrain. Enhancement of specific sulfatide species can be found in the fiber tracts and the molecular layer. Other lipid species are either mostly unchanging or slightly decreased, while they are increased in the frozen hydrated data. This would explain why ammonia treated spectra score further away from hydrated spectra in the PCA scores plot. Changes to the lipid signals other than the sulfatide species as a result of the freeze drying process are emphasized by ammonia treatment by reducing the nonsulfatide lipid signal intensity even further (lipid signal: FHFD > NH3). The reason for this decrease remains unclear. This effect is most pronounced in the fiber tracts and midbrain. The ratios were calculated using the normalized spectra, but comparisons of spectra with the absolute intensities show the same trends (see supplementary Figs. 1 and 4).29 The results of this study show that ammonia treatment leads to signal increase for some lipid species, mainly sulfatides. One could assume the suggested mechanism (exposing tissue sections to a proton acceptor in order to increase the deprotonated [MH] species present in the tissue) works, but considering all results, it appears this effect is minor compared to other influences, which alter the signal. After ammonia treatment, cholesterol crystals are still visible in SEM images, but cholesterol signal has dramatically decreased, close to frozen hydrated signal levels. SEM images comparing frozen hydrated (section were dried and at room temperature at the time of SEM analysis), freeze dried, ammonia, and TFA treated brain sections can be found in supplementary Fig. 8. It should be noted that the brain section that was analyzed frozen hydrated shows crystals in white matter areas as well, despite displaying cholesterol signal almost evenly distributed in the ToF-SIMS analysis as the tissue is now “dry” and in vacuum for the SEM imaging (supplementary Fig. 9). Therefore, we assume the main mechanism behind sulfatide and ceramide signal increase is the removal of cholesterol, which is either physically covering up the tissue underneath or reducing other signals due to matrix effects (or both). The reason why sulfatides and ceramides are increased beyond the levels of frozen hydrated


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FIG. 5. Table summarizing lipid changes as color coded ratios, compared to average spectra of their equivalent brain regions that were analyzed freeze dried. The columns are sorted according to sample treatment (60: 60 min NH3 exposure, FH: frozen hydrated, and TFA: 30 min TFA exposure) with subsections for different brain regions. Putative peak assignments are listed in column 2. Peaks are sorted according to their m/z ratio in column 3 and grouped together, exceptions are one sulfatide peak in the PS/PE/PA/SM segment, outlined in black, labeled with [s] and phosphoinositol peaks in the sulfatide area, outlined in red. Detailed information on numeric values for all ratios can be found in the supplementary material. Values for ratios represented by different colors are listed in the rightmost column.

signal levels could be that those species tend to migrate to the surface as well, like cholesterol, but are then being suppressed. The greater increase after 60 min, compared to 30 min, could be either due to increased cholesterol removal or increased deprotonation by the NH3. Single ion images showing the distribution of cholesterol and sulfatide signal are displayed in supplementary Fig. 9. The best indicator that ammonia is chemically influencing the sample in the intended way (proton transfer) is the slight decrease in the positive ion signal after 60 min treatment, compared to 30 min (supplementary Fig. 6). To get measurable increased deprotonation, ideally for all species, we might need to Biointerphases, Vol. 11, No. 2, June 2016

adjust our protocol, use ammonia exposure for a longer time period or in higher concentrations. E. Changes due to frozen hydrated analysis

Intact lipid species other than sulfatides (PS/phosphatidylethanolamine (PE)/PA/SM in Fig. 5) are enhanced in the frozen hydrated data set. Particularly, phosphoinositol signals are enhanced in the granular layer, the thalamus and to some extent in the isocortex. Different PS species are increased in the midbrain. Sulfatide signals are slightly decreased in most areas but increased in the midbrain. In the


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G. Special case of cholesterol

lower mass “lipid fragments and fatty acid” sections shown in Fig. 5, most signals are unchanged or slightly decreased apart from phosphoinositol fragments, which follow the trend of their parent ions. Apart from the sulfatide signals, frozen hydrated analysis shows the most intense signals for most lipids, signal increase is especially pronounced for phosphoinositol signals. The reasons are hypothesized to be minimal lipid migration; therefore, no signals are covered up; and water molecules still present in the tissue acting to enhance ionization, possibly ameliorating matrix effects. Overall, frozen hydrated, negative ion mode analysis shows the greatest chemical diversity in different areas. Areas displaying chemical differences in image PCA for frozen hydrated analysis (Fig. 1) can no longer be distinguished after freeze drying/ vapor exposure as shown in the results for spectral PCA (Fig. 2). Cholesterol signal is slightly elevated in the fiber tracts and depleted in the granular and pyramidal layer, which consist of mainly cell bodies. Therefore, by displaying sulfatides in the white matter and cholesterol everywhere where myelinated dendrites can be found, frozen hydrated analysis provides the best representation of the lipid distribution according to the biological literature.38–40

The changes in cholesterol signal are highlighted in Fig. 5, in the line marked as “Chol*” (m/z 385.4). In all brain regions, where cholesterol can be found in the freeze dried sample, the cholesterol signal is decreased due to any sample treatment with the biggest decrease observed when frozen hydrated analysis was performed. As discussed earlier, TFA spectra show a peak with similar mass, evenly distributed on the whole brain slide. This is an artifact due to TFA treatment and makes it appear as if cholesterol signal is increased in areas, where there is little or no cholesterol in the regions of the freeze dried data set. Analysis in positive ion mode and SEM images confirmed that cholesterol had been removed. Some studies suggest the issues due to cholesterol migration could be resolved by argon etching prior to the surface analysis.41 However, those studies were performed with dual beams, where the more destructive analysis beam probably aided the argon beam in breaking up the cholesterol crystals. Due to the “soft” sputtering characteristics of giant gas clusters and their reduced ability to sputter inorganic and crystalline material, using argon as sputter and analysis beam would lead to preferential sputtering of the areas free from cholesterol; therefore, reaching a steady state with this method on brain tissue would be difficult.

F. Changes due to TFA treatment

IV. CONCLUSIONS

Compared to all other sample treatments, the changes due to TFA treatment are the most pronounced. All areas apart from stratum radium and molecular layer show a huge increase in sulfatide and sulfatide fragment signal while all other signals are decreased. This decrease is expected due to TFA being an acidic compound providing the brain section with a surplus of protons; therefore, deprotonated species should decrease. The increase in sulfatides however results from a physical uncovering of these peaks as cholesterol is removed. Different from all other sample treatments, TFA exposure generates new, so far unidentified signals around m/z 1100. All other conditions produce only noise in that area of the spectrum and therefore show no variation when compared to freeze dried analysis. For sulfatides, we observed the same but even more pronounced trend as for the ammonia treatment; a substantial increase. That an acid is accepting extra protons and performs even better than a basic compound is highly unlikely; therefore, we assume the increase in sulfatide signals happens due to other changes. Equally, in positive ion mode, ammonia treatment elevates ceramide signals, as indicated by PCA loadings and spectra in positive ion mode supplementary Fig. 7 (increased by a factor of 2–4, data not shown) and does not change/decrease other signals significantly. (Increase in ceramide signals has been observed TFA treatment as well.9) All the evidence points at the main mechanism for spectra change being a result of cholesterol removal. After TFA treatment, cholesterol signals are no longer found in the spectrum as well as cholesterol crystals having vanished from the surface (SEM images).

ToF-SIMS is a very useful tool to explore location specific changes in brain chemistry and different means of multivariate analysis assist in discovering and identifying those changes. Knowing the influence that sample treatment can have on those changes is crucial. Frozen hydrated sample analysis is the best sample treatment to get an accurate lipid profile as it minimizes the chance of molecules migrating. However, if this is not possible ammonia vapor exposure is an option to broaden the scope of possible research questions, to be answered by using ToF-SIMS. These findings may have implications on disease studies related to cholesterol and demyelination. This study shows that if the cholesterol content in the brain was to decrease due to a specific condition, we would expect to detect elevated sulfatide signals in this area, but the increased sulfatide signal may not correspond to an increase in sulfatide content in the brain. The results suggest that sulfatides were present in all the tissues but masked. There is evidence that sulfatide levels and demyelination are connected.42,43 To study such changes using ToF-SIMS, it is clear that either frozen hydrated analysis is required or reproducible cholesterol removal is needed as is observed with TFA and NH3 exposure.

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ACKNOWLEDGMENT This work was performed at the National Centre for Imaging Mass Spectrometry, Sweden, part of the GU/Chalmers Bioanalytical Centre. 1 2

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